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Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition

Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition
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Field name Details
Dewey Class 519.5
Title Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition (EB) / by Haruo Yanai, Kei Takeuchi, Yoshio Takane.
Author Yanai, Haruo. , 1940-
Added Personal Name Takeuchi, Kei. , 1933-
Takane, Yoshio
Other name(s) SpringerLink (Online service)
Publication New York, NY : Springer , 2011.
Physical Details XII, 236 pages : online resource.
Series Statistics for Social and Behavioral Sciences
ISBN 9781441998873
Summary Note Aside from distribution theory, projections and the singular value decomposition (SVD) are the two most important concepts for understanding the basic mechanism of multivariate analysis. The former underlies the least squares estimation in regression analysis, which is essentially a projection of one subspace onto another, and the latter underlies principal component analysis, which seeks to find a subspace that captures the largest variability in the original space. This book is about projections and SVD. A thorough discussion of generalized inverse (g-inverse) matrices is also given because it is closely related to the former. The book provides systematic and in-depth accounts of these concepts from a unified viewpoint of linear transformations finite dimensional vector spaces. More specially, it shows that projection matrices (projectors) and g-inverse matrices can be defined in various ways so that a vector space is decomposed into a direct-sum of (disjoint) subspaces. Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition will be useful for researchers, practitioners, and students in applied mathematics, statistics, engineering, behaviormetrics, and other fields.:
Contents note Fundamentals of Linear Algebra -- Projection Matrices -- Generalized Inverse Matrices -- Explicit Representations -- Singular Value Decomposition (SVD) -- Various Applications.
System details note Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users).
Internet Site http://dx.doi.org/10.1007/978-1-4419-9887-3
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